Application-Oriented Performance Benchmarks for Quantum Computing (Part I)
ORAL
Abstract
In this work we introduce an open source suite of quantum application-oriented performance benchmarks that is designed to measure the effectiveness of quantum computing hardware at executing quantum applications. These benchmarks probe a quantum computer's performance on various algorithms and small applications as the problem size is varied, by mapping out the fidelity of the results as a function of circuit width and depth using the framework of volumetric benchmarking. In addition to estimating the fidelity of results generated by quantum execution, the suite is designed to benchmark certain aspects of the execution pipeline in order to provide end-users with a practical measure of both the quality of and the time to solution. Our methodology is constructed to anticipate advances in quantum computing hardware that are likely to emerge in the next five years. This benchmarking suite is designed to be readily accessible to a broad audience of users and provides benchmarks that correspond to many well-known quantum computing algorithms.
In part 1, we discuss the design choices for the set of benchmarks, including application-first selection of algorithms, quantum volume and volumetric benchmarks, and a noise-normalized fidelity metric.
In part 1, we discuss the design choices for the set of benchmarks, including application-first selection of algorithms, quantum volume and volumetric benchmarks, and a noise-normalized fidelity metric.
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Publication: https://arxiv.org/abs/2110.03137
Presenters
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Jason Necaise
D-Wave Systems
Authors
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Jason Necaise
D-Wave Systems
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Paul R Varosy
Colorado School of Mines
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Jeremiah D Coleman
Princeton University
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Tom Lubinski
Quantum Circuits, Inc
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Sonika Johri
IonQ, Inc
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Luning Zhao
IonQ
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Charles H Baldwin
Honeywell Quantum Solutions, Honeywell Intl
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Karl Mayer
Honeywell Quantum Solutions, Honeywell Intl
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Timothy J Proctor
Sandia National Laboratories